Neural latent representation of implicit perceptual decision confidence signatures from brain-wide intracranial EEG
- 1Indian Institute of Technology Guwahati; Ulster University
Abstract
Human perceptual decision confidence has been associated with brain-wide signalling, albeit with inconsistencies across studies. It remains unclear whether more robust neural latent representations exist, particularly for implicit confidence. We address this by applying complementary machine learning approaches to comprehensive, brain-wide intracranial electroencephalography (iEEG) data acquired without explicit confidence reports. Using explainable feature selection methods, we elucidated key spatiotemporal iEEG components, especially in the frontal cortex, that readily distinguished confidence characteristics related to decision correctness, difficulty, and speed, and that were transferable across motor modalities. Despite inconsistencies in the features identified across methods and conditions, dimensionality reductions revealed robust low-dimensional neural latent representations. Furthermore, their neural trajectories within a shared subspace enhanced the distinguishability of confidence characteristics. Overall, our results uncover low-dimensional spatial and temporal neural latent representations underlying human implicit perceptual decision confidence that are robust to analytical methods and decision conditions.
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BibTeX
@misc{mudavath2026neural,
title = {{Neural latent representation of implicit perceptual decision confidence signatures from brain-wide intracranial EEG}},
author = {U. K. N. Mudavath and A. Asadpour and S. Gherman and R. G. O'Connell and S. P. Kelly and S. Bickel and S. R. Ahamed and K. Wong-Lin},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.30.755781},
url = {https://www.biorxiv.org/content/10.64898/2026.09.30.755781v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Neural latent representation of implicit perceptual decision confidence signatures from brain-wide intracranial EEG
AU - U. K. N. Mudavath
AU - A. Asadpour
AU - S. Gherman
AU - R. G. O'Connell
AU - S. P. Kelly
AU - S. Bickel
AU - S. R. Ahamed
AU - K. Wong-Lin
PY - 2026
DA - 2026/09/30
PB - bioRxiv
DO - 10.64898/2026.09.30.755781
UR - https://www.biorxiv.org/content/10.64898/2026.09.30.755781v1
AB - Human perceptual decision confidence has been associated with brain-wide signalling, albeit with inconsistencies across studies. It remains unclear whether more robust neural latent representations exist, particularly for implicit confidence. We address this by applying complementary machine learning approaches to comprehensive, brain-wide intracranial electroencephalography (iEEG) data acquired without explicit confidence reports. Using explainable feature selection methods, we elucidated key spatiotemporal iEEG components, especially in the frontal cortex, that readily distinguished confidence characteristics related to decision correctness, difficulty, and speed, and that were transferable across motor modalities. Despite inconsistencies in the features identified across methods and conditions, dimensionality reductions revealed robust low-dimensional neural latent representations. Furthermore, their neural trajectories within a shared subspace enhanced the distinguishability of confidence characteristics. Overall, our results uncover low-dimensional spatial and temporal neural latent representations underlying human implicit perceptual decision confidence that are robust to analytical methods and decision conditions.
ER -